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1.
Journal of Chemistry ; : 1-10, 2022.
Article in English | Academic Search Complete | ID: covidwho-1840662

ABSTRACT

COVID-19 is causing havoc to human health and the world economy right now. It is a single standard positive-sense RNA virus which is transferred by inhalation of a viral droplet. Its genome forms four structural proteins such as nucleocapsid protein, membrane protein, spike protein, and envelop protein. The capsid of coronavirus is a protein shell within which a positive strand of RNA is present which enables the virus to control the machinery of human cells. It has several variants, e.g., SARS, MERS, and now a new variant identified in 2019, which is a novel coronavirus that causes novel coronavirus disease (COVID-19). COVID-19 is a novel coronavirus disease that originally arose in Wuhan, China, and quickly spread around the world. Clinically, we identified the virus presence by a PCR-based test. Preventive measures and vaccination are the only treatment against coronavirus. Some of these include Remdesivir (GS-5734), Chloroquine, Hydroxychloroquine, and Theaflavin. A topological index (TI) is a mathematical function that assigns a numerical value to a (molecular) graph and predicts many physical, chemical, biological, thermodynamical, and structural features of that network. In this work, we will calculate a new topological index, namely, the first and second Gourava and Hyper-Gourava indices for the molecular graph of Remdesivir (GS-5734), Chloroquine, Hydroxychloroquine, and Theaflavin. We also plotted our computed results to examine how they were affected by the parameters involved. These findings could contribute in the development of new COVID-19 therapy options. [ FROM AUTHOR] Copyright of Journal of Chemistry is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

2.
Sci Rep ; 12(1): 5751, 2022 04 06.
Article in English | MEDLINE | ID: covidwho-1784019

ABSTRACT

We deal in this paper with a diffusive SIR epidemic model described by reaction-diffusion equations involving a fractional derivative. The existence and uniqueness of the solution are shown, next to the boundedness of the solution. Further, it has been shown that the global behavior of the solution is governed by the value of [Formula: see text], which is known in epidemiology by the basic reproduction number. Indeed, using the Lyapunov direct method it has been proved that the disease will extinct for [Formula: see text] for any value of the diffusion constants. For [Formula: see text], the disease will persist and the unique positive equilibrium is globally stable. Some numerical illustrations have been used to confirm our theoretical results.


Subject(s)
Epidemics , Basic Reproduction Number , Models, Biological
3.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-304969

ABSTRACT

Recently, novel coronavirus is a serious global issue and having a negative impact on the economy of the whole world. Like other countries, it also effected the economy and people of Pakistan. According to the publicly reported data, the first case of novel corona virus in Pakistan was reported on 27 th February 2020. The aim of the present study is to describe the mathematical model and dynamics of COVID-19 in Pakistan. To investigate the spread of coronavirus in Pakistan, we develop the SEIR time fractional model with newly, developed fractional operator of Atangana-Baleanu. We present briefly the analysis of the given model and discuss its applications using world health organization (WHO) reported data for Pakistan. We consider the available infection cases from 19 th march 2020, till 31 st march 2020 and accordingly, various parameters are fitted or estimated. It is worth noting that we have calculated the basic reproduction number which shows that virus is spreading rapidly. Furthermore, stability analysis of the model at disease free equilibrium DFE and endemic equilibriums EE is performed to observe the dynamics and transmission of the model. Finally, the AB fractional model is solved numerically. To show the effect of the various embedded parameters like fractional parameter on the model, various graphs are plotted. It is worth noting that the base of our investigation, we have predicted the spread of disease for next 200 days.

4.
Results Phys ; 28: 104598, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1331208

ABSTRACT

The novel Coronavirus Disease 2019 (COVID-19) is a highly infectious disease caused by a new strain of severe acute respiratory syndrome of coronavirus 2 (SARS-CoV-2). In this work, we proposed a mathematical model of COVID-19. We carried out the qualitative analysis along with an epidemic indicator which is the basic reproduction number ( R 0 ) of this model, stability analysis of COVID-19 free equilibrium (CFE) and Endemic equilibrium (EE) using Lyaponuv function are considered. We extended the basic model into optimal control system by incorporating three control strategies. These are; use of face-mask and hand sanitizer along with social distancing; treatment of COVID-19 patients and active screening with testing and the third control is prevention against recurrence and reinfection of humans who have recovered from COVID-19. Daily data given by Nigeria Center for Disease Control (NCDC) in Nigeria is used for simulation of the proposed COVID-19 model to see the effects of the control measures. The biological interpretation of this findings is that, COVID-19 can be effectively managed or eliminated in Nigeria if the control measures implemented are capable of taking or sustaining the basic reproductive number R 0 to a value below unity. If the three control strategies are well managed by the government namely; NCDC, Presidential Task Force (PTF) and Federal Ministry of Health (FMOH) or policymakers, then COVID-19 in Nigeria will be eradicated.

5.
Alexandria Engineering Journal ; 2021.
Article in English | ScienceDirect | ID: covidwho-1275066

ABSTRACT

The present study is conducted to analyse the computational dynamical analysis of the stochastic susceptible-infected-recovered pandemic model of the novel coronavirus. We adopted two ways for stochastic modelling like as transition probabilities and parametric perturbation techniques. We applied different and well-known computational methods like Euler Maruyama, stochastic Euler, and stochastic Runge Kutta to study the dynamics of the model mentioned above. Unfortunately, these computational methods do not restore the dynamical properties of the model like positivity, boundedness, consistency, and stability in the sense of biological reasoning, as desired. Then, for the given stochastic model, we developed a stochastic non-standard finite difference method. Following that, several theorems are presented to support the proposed method, which is shown to satisfy all of the model's dynamical properties. To that end, several simulations are presented to compare the proposed method's efficiency to that of existing stochastic methods.

6.
Results Phys ; 26: 104260, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1240601

ABSTRACT

In this research article, we establish a fractional-order mathematical model to explore the infections of the coronavirus disease (COVID-19) caused by the novel SARS-CoV-2 virus. We introduce a set of fractional differential equations taking uninfected epithelial cells, infected epithelial cells, SARS-CoV-2 virus, and CTL response cell accounting for the lytic and non-lytic effects of immune responses. We also include the effect of a commonly used antiviral drug in COVID-19 treatment in an optimal control-theoretic approach. The stability of the equilibria of the fractional ordered system using qualitative theory. Numerical simulations are presented using an iterative scheme in Matlab in support of the analytical results.

7.
Computers, Materials, & Continua ; 67(3):2933-2953, 2021.
Article | ProQuest Central | ID: covidwho-1112960

ABSTRACT

Recently, the world is facing the terror of the novel corona-virus, termed as COVID-19. Various health institutes and researchers are continuously striving to control this pandemic. In this article, the SEIAR (susceptible, exposed, infected, symptomatically infected, asymptomatically infected and recovered) infection model of COVID-19 with a constant rate of advection is studied for the disease propagation. A simple model of the disease is extended to an advection model by accommodating the advection process and some appropriate parameters in the system. The continuous model is transposed into a discrete numerical model by discretizing the domains, finitely. To analyze the disease dynamics, a structure preserving non-standard finite difference scheme is designed. Two steady states of the continuous system are described i.e., virus free steady state and virus existing steady state. Graphical results show that both the steady states of the numerical design coincide with the fixed points of the continuous SEIAR model. Positivity of the state variables is ensured by applying the M-matrix theory. A result for the positivity property is established. For the proposed numerical design, two different types of the stability are investigated. Nonlinear stability and linear stability for the projected scheme is examined by applying some standard results. Von Neuman stability test is applied to ensure linear stability. The reproductive number is described and its pivotal role in stability analysis is also discussed. Consistency and convergence of the numerical model is also studied. Numerical graphs are presented via computer simulations to prove the worth and efficiency of the quarantine factor is explored graphically, which is helpful in controlling the disease dynamics. In the end, the conclusion of the study is also rendered.

8.
Computers, Materials, & Continua ; 66(3):2787-2796, 2021.
Article in English | ProQuest Central | ID: covidwho-1005405

ABSTRACT

In this study, we have proposed an artificial neural network (ANN) model to estimate and forecast the number of confirmed and recovered cases of COVID-19 in the upcoming days until September 17, 2020. The proposed model is based on the existing data (training data) published in the Saudi Arabia Coronavirus disease (COVID-19) situation—Demographics. The Prey-Predator algorithm is employed for the training. Multilayer perceptron neural network (MLPNN) is used in this study. To improve the performance of MLPNN, we determined the parameters of MLPNN using the prey-predator algorithm (PPA). The proposed model is called the MLPNN–PPA. The performance of the proposed model has been analyzed by the root mean squared error (RMSE) function, and correlation coefficient (R). Furthermore, we tested the proposed model using other existing data recorded in Saudi Arabia (testing data). It is demonstrated that the MLPNN-PPA model has the highest performance in predicting the number of infected and recovering in Saudi Arabia. The results reveal that the number of infected persons will increase in the coming days and become a minimum of 9789. The number of recoveries will be 2000 to 4000 per day.

9.
Sci Rep ; 10(1): 22268, 2020 12 17.
Article in English | MEDLINE | ID: covidwho-989961

ABSTRACT

Recently, novel coronavirus is a serious global issue and having a negative impact on the economy of the whole world. Like other countries, it also effected the economy and people of Pakistan. According to the publicly reported data, the first case of novel corona virus in Pakistan was reported on 27th February 2020. The aim of the present study is to describe the mathematical model and dynamics of COVID-19 in Pakistan. To investigate the spread of coronavirus in Pakistan, we develop the SEIR time fractional model with newly, developed fractional operator of Atangana-Baleanu. We present briefly the analysis of the given model and discuss its applications using world health organization (WHO) reported data for Pakistan. We consider the available infection cases from 19th March 2020, till 31st March 2020 and accordingly, various parameters are fitted or estimated. It is worth noting that we have calculated the basic reproduction number [Formula: see text] which shows that virus is spreading rapidly. Furthermore, stability analysis of the model at disease free equilibrium DFE and endemic equilibriums EE is performed to observe the dynamics and transmission of the model. Finally, the AB fractional model is solved numerically. To show the effect of the various embedded parameters like fractional parameter [Formula: see text] on the model, various graphs are plotted. It is worth noting that the base of our investigation, we have predicted the spread of disease for next 200 days.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Epidemics/statistics & numerical data , Humans , Models, Theoretical , Pakistan/epidemiology , SARS-CoV-2/pathogenicity , World Health Organization
10.
Computers, Materials, & Continua ; 66(2):1977-1985, 2021.
Article in English | ProQuest Central | ID: covidwho-954689

ABSTRACT

The flow of novel coronavirus (COVID-19) has affected almost every aspect of human life around the globe. Being the emerging ground and early sufferer of the virus, Wuhan city-data remains a case of multifold significance. Further, it is of notable importance to explore the impact of unique and unprecedented public health response of Chinese authorities—the extreme lockdown of the city. In this research, we investigate the statistical nature of the viral transmission concerning social distancing, extreme quarantine, and robust lockdown interventions. We observed highly convincing and statistically significant evidences in favor of quarantine and social distancing approaches. These findings might help countries, now facing, or likely to face the wave of the virus. We analyzed Wuhan-based data of “number of deaths” and “confirmed cases,” extracted from China CDC weekly database, dated from February 13, 2020, to March 24, 2020. To estimate the underlying group structure, the assembled data is further sub-divided into three blocks, each consists of two weeks. Thus, the complete data set is studied in three phases, such as, phase 1 (Ph 1) = February 13, 2020, to February 26, 2020;phase 2 (Ph 2) = February 27, 2020 to March 11, 2020;and phase 3 (Ph 3) = March 12, 2020 to March 24, 2020. We observed the overall median proportion of deaths in those six weeks remained 0.0127. This estimate is highly influenced by Ph1, when the early flaws of weak health response were still prevalent. Over the time, we witnessed a median decline of 92.12% in the death proportions. Moreover, a non-parametric version of the variability analysis of death data, estimated that the average rank of reported proportions in Ph 3 remained 7, which was 20.5 in Ph 2, and stayed 34.5 in the first phase. Similar patterns were observed, when studying the confirmed cases data. We estimated the overall median of the proportion of confirmed cases in Wuhan as 0.0041, which again, is highly inclined towards Ph 1 and Ph 2. We also witnessed minimum average rank proportions for Ph 3, such as 7, which was noticeably lower than Ph 2, 21.71, and Ph 1, 32.29. Moreover, the varying degree of clustering indicates that the effectiveness of quarantine based policies is time-dependent. In general, the decline in coronavirus transmission in Wuhan significantly coincides with the lockdown.

11.
Computers, Materials, & Continua ; 66(2):1823-1848, 2021.
Article in English | ProQuest Central | ID: covidwho-953583

ABSTRACT

We propose a mathematical model of the coronavirus disease 2019 (COVID-19) to investigate the transmission and control mechanism of the disease in the community of Nigeria. Using stability theory of differential equations, the qualitative behavior of model is studied. The pandemic indicator represented by basic reproductive number R0 is obtained from the largest eigenvalue of the next-generation matrix. Local as well as global asymptotic stability conditions for the disease-free and pandemic equilibrium are obtained which determines the conditions to stabilize the exponential spread of the disease. Further, we examined this model by using Atangana–Baleanu fractional derivative operator and existence criteria of solution for the operator is established. We consider the data of reported infection cases from April 1, 2020, till April 30, 2020, and parameterized the model. We have used one of the reliable and efficient method known as iterative Laplace transform to obtain numerical simulations. The impacts of various biological parameters on transmission dynamics of COVID-19 is examined. These results are based on different values of the fractional parameter and serve as a control parameter to identify the significant strategies for the control of the disease. In the end, the obtained results are demonstrated graphically to justify our theoretical findings.

12.
mBio ; 11(5)2020 09 15.
Article in English | MEDLINE | ID: covidwho-772275

ABSTRACT

Membrane-associated RING-CH-type 8 (MARCH8) strongly blocks human immunodeficiency virus type 1 (HIV-1) envelope glycoprotein (Env) incorporation into virions by downregulating its cell surface expression, but the mechanism is still unclear. We now report that MARCH8 also blocks the Ebola virus (EBOV) glycoprotein (GP) incorporation via surface downregulation. To understand how these viral fusion proteins are downregulated, we investigated the effects of MARCH8 on EBOV GP maturation and externalization via the conventional secretion pathway. MARCH8 interacted with EBOV GP and furin when detected by immunoprecipitation and retained the GP/furin complex in the Golgi when their location was tracked by a bimolecular fluorescence complementation (BiFC) assay. MARCH8 did not reduce the GP expression or affect the GP modification by high-mannose N-glycans in the endoplasmic reticulum (ER), but it inhibited the formation of complex N-glycans on the GP in the Golgi. Additionally, the GP O-glycosylation and furin-mediated proteolytic cleavage were also inhibited. Moreover, we identified a novel furin cleavage site on EBOV GP and found that only those fully glycosylated GPs were processed by furin and incorporated into virions. Furthermore, the GP shedding and secretion were all blocked by MARCH8. MARCH8 also blocked the furin-mediated cleavage of HIV-1 Env (gp160) and the highly pathogenic avian influenza virus H5N1 hemagglutinin (HA). We conclude that MARCH8 has a very broad antiviral activity by prohibiting different viral fusion proteins from glycosylation and proteolytic cleavage in the Golgi, which inhibits their transport from the Golgi to the plasma membrane and incorporation into virions.IMPORTANCE Enveloped viruses express three classes of fusion proteins that are required for their entry into host cells via mediating virus and cell membrane fusion. Class I fusion proteins are produced from influenza viruses, retroviruses, Ebola viruses, and coronaviruses. They are first synthesized as a type I transmembrane polypeptide precursor that is subsequently glycosylated and oligomerized. Most of these precursors are cleaved en route to the plasma membrane by a cellular protease furin in the late secretory pathway, generating the trimeric N-terminal receptor-binding and C-terminal fusion subunits. Here, we show that a cellular protein, MARCH8, specifically inhibits the furin-mediated cleavage of EBOV GP, HIV-1 Env, and H5N1 HA. Further analyses uncovered that MARCH8 blocked the EBOV GP glycosylation in the Golgi and inhibited its transport from the Golgi to the plasma membrane. Thus, MARCH8 has a very broad antiviral activity by specifically inactivating different viral fusion proteins.


Subject(s)
Ebolavirus/chemistry , Glycoproteins/antagonists & inhibitors , HIV-1/chemistry , Hemagglutinins, Viral/metabolism , Influenza A Virus, H5N1 Subtype/chemistry , Ubiquitin-Protein Ligases/genetics , Viral Envelope Proteins/antagonists & inhibitors , Viral Envelope Proteins/physiology , Animals , Cell Line , Chlorocebus aethiops , Ebolavirus/physiology , Glycosylation , HEK293 Cells , HIV-1/physiology , HeLa Cells , Hep G2 Cells , Humans , Influenza A Virus, H5N1 Subtype/physiology , Protein Binding , THP-1 Cells , Ubiquitin-Protein Ligases/metabolism , Vero Cells , Viral Fusion Proteins/antagonists & inhibitors , Viral Fusion Proteins/metabolism
13.
Cmc-Computers Materials & Continua ; 64(3):1401-1414, 2020.
Article | WHO COVID | ID: covidwho-732587

ABSTRACT

In this manuscript, the mathematical analysis of corona virus model with time delay effect is studied. Mathematical modelling of infectious diseases has substantial role in the different disciplines such as biological, engineering, physical, social, behavioural problems and many more. Most of infectious diseases are dreadful such as HIV/AIDS, Hepatitis and 2019-nCov. Unfortunately, due to the non-availability of vaccine for 2019-nCov around the world, the delay factors like, social distancing, quarantine, travel restrictions, holidays extension, hospitalization and isolation are used as key tools to control the pandemic of 2019-nCov. We have analysed the reproduction number R-nCov of delayed model. Two key strategies from the reproduction number of 2019-nCov model, may be followed, according to the nature of the disease as if it is diminished or present in the community. The more delaying tactics eventually, led to the control of pandemic. Local and global stability of 2019-nCov model is presented for the strategies. We have also investigated the effect of delay factor on reproduction number R-nCov. Finally, some very useful numerical results are presented to support the theoretical analysis of the model.

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